Numerical optimization
Numerical Optimization presents a comprehensive and up-to-date description of the most effective methods in continuous optimization. It responds to the growing interest in optimization in engineering, science, and business by focusing on the methods that are best suited to practical problems. For th...
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| Hlavní autoři: | , |
|---|---|
| Médium: | Livre numérique |
| Jazyk: | Anglais |
| Vydáno: |
New York, NY :
Springer New York
[20..].
Cham : Springer Nature |
| Vydání: | 2nd Edition. |
| Edice: | Springer Series in Operations Research and Financial Engineering
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| Témata: | |
| On-line přístup: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Poznámka: |
Description d'après consultation du 14 avril 2011 Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Numerical Optimization, Texte imprimé, 9780387510880 • Numerical optimization, Jorge Nocedal, Stephen J. Wright, 2nd edition, 2006, New York, Springer, 1 volume (xxii-664 pages), Springer Series in Operations Research and Financial Engineering, 978-0387-30303-1 • Numerical Optimization, Texte imprimé, 9781493937110 |
Obsah:
- Fundamentals of Unconstrained Optimization Line Search Methods Trust-Region Methods Conjugate Gradient Methods Quasi-Newton Methods Large-Scale Unconstrained Optimization Calculating Derivatives Derivative-Free Optimization Least-Squares Problems Nonlinear Equations Theory of Constrained Optimization Linear Programming: The Simplex Method Linear Programming: Interior-Point Methods Fundamentals of Algorithms for Nonlinear Constrained Optimization Quadratic Programming Penalty and Augmented Lagrangian Methods Sequential Quadratic Programming Interior-Point Methods for Nonlinear Programming.
- 1. Introduction
- 2. Fundamentals of unconstrained optimization
- 3. Line search methods
- 4. Trust-region methods
- 5. Conjugate gradient methods
- 6. Quasi-Newton methods
- 7. Large-scale unconstrained optimization
- 8. Calculating derivatives
- 9. Derivative-free optimization
- 10. Least-squares problems
- 11. Nonlinear equations
- 12. Theory of constrained optimization
- 13. Linear programming : the simplex method
- 14. Linear programming : interior-point methods
- 15. Fundamentals of algorithms for nonlinear constrained optimization
- 16. Quadratic programming
- 17. Penalty and augmented Lagrangian methods
- 18. Sequential quadratic programming
- 19. Interior-point methods for nonlinear programming